Abstract
Aim: Our aim was to identify multimorbidity clusters and, in particular, to examine their contribution to well-being outcomes among the oldest old in Germany. Methods: Data were taken from the large nationally representative D80+ study including community-dwelling and institutionalized individuals aged 80 years and over residing in Germany (n = 8,773). The mean age was 85.6 years (SD: 4.1). Based on 21 chronic conditions, latent class analysis was carried out to explore multimorbidity (≥2 chronic conditions) clusters. Widely used tools were applied to quantify well-being outcomes. Results: Approximately nine out of ten people aged 80 and over living in Germany were multimorbid. Four multimorbidity clusters were identified: relatively healthy class (30.2 %), musculoskeletal class (44.8 %), mental illness class (8.6 %), and high morbidity class (16.4 %). Being part of the mental disorders cluster was consistently linked to reduced well-being (in terms of low life satisfaction, high loneliness and lower odds of meaning in life), followed by membership in the high morbidity cluster. Conclusions: Four multimorbidity clusters were detected among the oldest old in Germany. Particularly belonging to the mental disorders cluster is consistently associated with low well-being, followed by belonging to the high morbidity cluster. This stresses the need for efforts to target such vulnerable groups, pending future longitudinal research.
| Original language | English |
|---|---|
| Article number | 105726 |
| Journal | Archives of Gerontology and Geriatrics |
| Volume | 130 |
| DOIs | |
| Publication status | Published - Mar 2025 |
| Externally published | Yes |
Keywords
- Depression
- High morbidity
- Latent class analysis
- Life satisfaction
- Loneliness
- Mental health
- Mental illness
- Multimorbidity clusters
- Multimorbidity patterns
- Multiple chronic conditions
- Oldest old
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